produce a flextable describing a generalized linear model produced by function glm.

# S3 method for glm
as_flextable(x, ...)

Arguments

x

glm model

...

unused argument

Illustrations

See also

Examples

if(require("broom")){
  dat <- attitude
  dat$high.rating <- (dat$rating > 70)
  probit.model <- glm(high.rating ~ learning + critical +
     advance, data=dat, family = binomial(link = "probit"))
  ft <- as_flextable(probit.model)
  ft
}
#> Loading required package: broom
#> a flextable object.
#> col_keys: `term`, `estimate`, `std.error`, `statistic`, `p.value`, `signif` 
#> header has 1 row(s) 
#> body has 4 row(s) 
#> original dataset sample: 
#>          term     estimate  std.error   statistic     p.value signif
#> 1 (Intercept) -7.476392694 3.57018899 -2.09411679 0.036249578       
#> 2    learning  0.164374512 0.05337819  3.07943220 0.002073956       
#> 3    critical -0.000571721 0.04390146 -0.01302283 0.989609583       
#> 4     advance -0.061879215 0.04203589 -1.47205666 0.141005579